class_docstr: Class for Euclidean metrics.
  
  As a Riemannian metric, the Euclidean metric is:
  
  - flat: the inner-product is independent of the base point;
  - positive definite: it has signature (dimension, 0, 0),
    where dimension is the dimension of the Euclidean space.
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docstr: Compute log map using a base point and other point.
  
  The Riemannian logarithm is the subtraction in the Euclidean space.
  
  Parameters
  ----------
  point: array-like, shape=[..., dim]
      Point.
  base_point: array-like, shape=[..., dim]
      Base point.
  
  Returns
  -------
  log: array-like, shape=[..., dim]
      Riemannian logarithm.
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code: def log(self, point, base_point, **kwargs):
      """Compute log map using a base point and other point.
  
      The Riemannian logarithm is the subtraction in the Euclidean space.
  
      Parameters
      ----------
      point: array-like, shape=[..., dim]
          Point.
      base_point: array-like, shape=[..., dim]
          Base point.
  
      Returns
      -------
      log: array-like, shape=[..., dim]
          Riemannian logarithm.
      """
      return point - base_point
  
file_path: geomstats/geomstats/geometry/euclidean.py
imports: import geomstats.backend
  from geomstats.geometry.base import VectorSpace
  from geomstats.geometry.riemannian_metric import RiemannianMetric
  from geomstats.vectorization import repeat_out
label_desc: Use image node_id 5 for calling the EuclideanMetric obj's underlying member method code with example usage: obj.log(point, base_point) and returns: unknown